1. Field of the Invention
The present invention relates to a sound signal correcting method for correcting a sound signal based on acquired sound, on the basis of a noise model relating to a noise pattern, a sound signal correcting apparatus to which this sound signal correcting method is applied, and a computer program for implementing this sound signal correcting apparatus. In particular, the present invention relates to a sound signal correcting method in which the recognition ratio of voice for the acquired sound is increased, a sound signal correcting apparatus and a computer program.
2. Description of Related Art
Noise suppressing technology for suppressing a noise component in sound acquired under an environment with noise is used for the purpose of increasing the recognition ratio of voice in speech recognizing apparatuses, such as car navigation devices, and increasing the quality of apparatuses relating to voice, for example increasing the quality of sending voice in phones.
FIG. 1 is a diagram conceptually showing conventional noise suppressing technology. According to conventional noise suppressing technology, sound including noise and voice is acquired, and a sound signal based on the acquired sound on a frame-by-frame basis, which is an input signal in(n), is converted into a phase spectrum tan−1 IN(f) and an amplitude spectrum |IN(f)| by an FFT (Fast Fourier Transformation) process. Then, an amplitude spectrum |N(f)| of stationary noise is estimated on the basis of a noise model having a high degree of similarity with the amplitude spectrum |IN(f)| of the sound signal, and the estimated amplitude spectrum |N(f)| of stationary noise is subtracted from the amplitude spectrum |IN(f)| of the sound signal. Then, the amplitude spectrum |IN(f)| from which the amplitude spectrum |N(f)| of stationary noise has been subtracted and the phase spectrum tan−1 IN(f) are converted by an inverse FFT process, and thereby, an output signal out(n) in each frame is derived. The derived output signal is used for processing, for example speech recognition, as a sound signal where noise is suppressed.
FIGS. 2A and 2B are diagrams showing an amplitude spectrum relating to conventional noise suppressing technology. FIG. 2A shows the relationship between the values of frequency and amplitude in the amplitude spectrum |IN(f)| of a sound signal, and FIG. 2B shows the relationship between the values of frequency and amplitude in the amplitude spectrum |IN(f)| from which the amplitude spectrum |N(f)| of stationary noise has been subtracted. As is clear when FIGS. 2A and 2B are compared, the estimated amplitude spectrum |N(f)| of stationary noise has been subtracted from the amplitude spectrum |IN(f)| of an input signal in the waveform shown in FIG. 2B, and thereby, noise is suppressed. Such noise suppressing technology is referred to as spectral subtraction, and noise suppressing technology using spectral subtraction is disclosed in, for example, Japanese Patent Application Laid-Open No. 07-193548 (1995).